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Nikolov, Andriy and d'Aquin, Mathieu
(2011).
Abstract
With more data repositories constantly being published on the Web, choosing appropriate data sources to interlink with newly published datasets becomes a non-trivial problem. While catalogs of data repositories and meta-level descriptors such as VoiD provide valuable information to take these decisions, more detailed information about the instances included into repositories is often required to assess the relevance of datasets and the part of the dataset to link to. However, retrieving and processing such information for a potentially large number of datasets is practically unfeasible. In this paper, we examine how using an existing semantic web index can help identifying candidate datasets for linking. We further apply ontology schema matching techniques to rank these candidate datasets and extract the sub-dataset to use for linking, in the form of classes with instances more likely to match the ones of the local dataset.
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- Item ORO ID
- 29298
- Item Type
- Conference or Workshop Item
- Project Funding Details
-
Funded Project Name Project ID Funding Body Not Set Not Set EC 7th Framework Programme, in the context of the SmartProducts project (231204) - Keywords
- data fusion; data linking; linked data
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Research Group
- Centre for Research in Computing (CRC)
- Copyright Holders
- © The Author/owner(s)
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- Depositing User
- Kay Dave